InfluxData, creator of the time series database InfluxDB, today announced the general availability of the next-generation open source platform for time series data, InfluxDB 2.0. Developers can now ingest, query, store and visualize time series data in a single unified platform, leverage new tools and integrations, and use familiar skills — making it faster and easier than ever to develop and deploy modern time-based applications. In addition, the company announced a new open source project to reimagine storage.
The amount of data being produced is expected to grow exponentially from 45 zettabytes in 2019 to 175ZB in 2025, primarily from applications, networks, containers, and a projected 60 billion IoT devices — and most of this is time-stamped data (IDC, 2020). While there is a tremendous opportunity for organizations to leverage this data to enhance customer experiences, improve employee and process productivity, and to create competitive advantage, it will be challenging to store and analyze the large volumes and high-frequency streams of data. These workloads will require rapid ingestion, advanced querying, and edge processing to maintain resource and cost efficiency, and maximize the value to end users. InfluxDB 2.0 is built to handle these data challenges of the future.
InfluxDB 2.0 is a time series platform for building IoT, analytics and monitoring applications powered by time series data. New features in InfluxDB 2.0 are designed to reduce the amount of time developers spend writing code to get started and manage existing projects, including:
- Flux – the first functional query and programming language built specifically for time series data, which makes it possible to enrich and transform data, build forecasts, and identify anomalies and correlations
- InfluxDB Templates – a growing gallery of single-file monitoring configurations for common use cases, like network and IoT sensor monitoring, that allow users to share their expertise and get up and monitoring in minutes
- Edge functionality – able to aggregate and analyze time series data at the point of ingestion, where it’s most valuable to take action
- Client libraries – support for writing and querying from popular languages, dramatically easing integration with other applications and empowering teams to use existing programming language skills
InfluxDB 2.0 is also tightly integrated with InfluxDB Cloud, the serverless, elastically scalable, fully managed time series database platform. With a shared API, it’s easy to move data and workloads between InfluxDB 2.0 and InfluxDB Cloud, and powerful to use them together as components of a single time series platform designed to give developers the flexibility and tools to meet changing business and application requirements.
“Developers today are looking for open source software, delivered as a managed service,” said James Governor, RedMonk co-founder. “InfluxDB 2.0 responds to this convergence with an integrated OSS, edge and cloud services play designed to make it easier to build and manage high-scale time series-based applications.”
The company also unveiled plans for the next-generation storage engine — project InfluxDB IOx. InfluxDB IOx is a new powerful storage engine designed to execute increasing query workloads over time. InfluxDB IOx lifts restrictions on cardinality, data size and cluster size that are inherent in the open source version of InfluxDB 2.0 — expanding the possibilities for workloads across thousands of servers and petabytes of data — a significant jump from current and other product allowances. Most time series solutions are designed around a rigid database structure, which limits the ability to work with high-cardinality data, but InfluxDB IOx separates storage from compute by using object storage as the durability layer and a management layer to control many stateless query, ingest, and indexing servers running ephemerally in Kubernetes. It also significantly broadens the InfluxDB ecosystem using industry-standard protocols and persistence, like Apache Arrow Flight and Apache Parquet. The InfluxDB IOx project expands the permissiveness of open source and is dual-licensed with MIT and Apache 2.0 to emphasize InfluxData’s commitment to pure open source. Dix opened the InfluxDB IOx project codebase repository during his talk at InfluxDays North America and now welcomes comments.
“We’re driven by our commitment to developer productivity and are eager for our community to start using InfluxDB 2.0 so they can start doing more with time series data,” said Paul Dix, CTO and founder of InfluxData. ”But InfluxDB 2.0 is just the start of our journey. We want developers to build awesome apps with our open source software, uninhibited by licensing restrictions and limitations.”
InfluxDB 2.0 is MIT License permissive — one of the most liberal open source licenses. InfluxDB 2.0 is the successor to InfluxDB 1.0, which was made generally available in September 2016. Over the last four years, there have been millions of downloads of the open source software and there are currently more than 400,000 daily active instances around the world.
It’s quick and easy to get started with InfluxDB 2.0. For existing InfluxDB users, it’s a seamless upgrade from 1.x versions that can be done by downloading InfluxDB 2.0 and running a single command to transfer data. New users can get started by downloading and installing InfluxDB 2.0, and can be collecting time series data in under one minute.
InfluxData is the creator of InfluxDB, the leading time series platform. We empower developers and organizations, such as Cisco, IBM, Lego, Siemens, and Tesla, to build transformative IoT, analytics and monitoring applications. Our technology is purpose-built to handle the massive volumes of time-stamped data produced by sensors, applications and computer infrastructure. Easy to start and scale, InfluxDB gives developers time to focus on the features and functionalities that give their apps a competitive edge. InfluxData is headquartered in San Francisco with a workforce distributed throughout the U.S. and across Europe. For more information, visit www.influxdata.com and follow us @InfluxDB.